Evaluation of women's aging influence on sperm passage inside the fallopian tube using 3D dynamic mechanical modeling.

The fallopian tubes play an important role in human fertility by facilitating the spermatozoa passage to the oocyte as well as later actively facilitating the fertilized oocyte transportation to the uterus cavity. The fallopian tubes undergo changes involving biological, physical, and morphological processes due to women aging, which may impair fertility. Here, we have modelled fallopian tubes of women at different ages and evaluated the chances of normal and pathological sperm cells reaching the fertilization site, the ampulla. By utilizing a unique combination of simulative tools, we implemented dynamic three-dimensional (3D) detailed geometrical models of many normal and pathological sperm cells swimming together in 3D geometrical models of three fallopian tubes associated with different women's age groups. By tracking the sperm cell swim, we found that for all age groups, the number of normal sperm cells in the ampulla is the largest, compared with the pathological sperm cells. On the other hand, the number of normal sperm cells in the fertilization site decreases due to the morphological and mechanical changes that occur in the fallopian tube with age. Moreover, in older ages, the normal sperm cells swim with lower velocities and for shorter distances inside the ampulla toward the ovary. Thus, the changes that the human fallopian tube undergoes due to women's aging have a significant influence on the human sperm cell motility. Our model of sperm cell motility through the fallopian tube in relation to the woman's age morphological changes provides a new scope for the investigation and treatment of diseases and infertility cases associated with aging, as well as a potential personalized medicine tool for evaluating the chances of a natural fertilization per specific features of a man's sperm and a woman's reproductive system.

Experimental and virtual testing of bone-implant systems equipped with the AO Fracture Monitor with regard to interfragmentary movement.

Introduction: The management of fractured bones is a key domain within orthopedic trauma surgery, with the prevention of delayed healing and non-unions forming a core challenge. This study evaluates the efficacy of the AO Fracture Monitor in conjunction with biomechanical simulations to better understand the local mechanics of fracture gaps, which is crucial for comprehending mechanotransduction, a key factor in bone healing. Through a series of experiments and corresponding simulations, the study tests four hypotheses to determine the relationship between physical measurements and the predictive power of biomechanical models. Methods: Employing the AO Fracture Monitor and Digital Image Correlation techniques, the study demonstrates a significant correlation between the surface strain of implants and interfragmentary movements. This provides a foundation for utilizing one-dimensional AO Fracture Monitor measurements to predict three-dimensional fracture behavior, thereby linking mechanical loading with fracture gap dynamics. Moreover, the research establishes that finite element simulations of bone-implant systems can be effectively validated using experimental data, underpinning the accuracy of simulations in replicating physical behaviors. Results and Discussion: The findings endorse the combined use of monitoring technologies and simulations to infer the local mechanical conditions at the fracture site, offering a potential leap in personalized therapy for bone healing. Clinically, this approach can enhance treatment outcomes by refining the assessment precision in trauma trials, fostering the early detection of healing disturbances, and guiding improvements in future implant design. Ultimately, this study paves the way for more sophisticated patient monitoring and tailored interventions, promising to elevate the standard of care in orthopedic trauma surgery.

Automated tooth crown design with optimized shape and biomechanics properties.

Despite the large demand for dental restoration each year, the design of crown restorations is mainly performed via manual software operation, which is tedious and subjective. Moreover, the current design process lacks biomechanics optimization, leading to localized stress concentration and reduced working life. To tackle these challenges, we develop a fully automated algorithm for crown restoration based on deformable model fitting and biomechanical optimization. From a library of dental oral scans, a conditional shape model (CSM) is constructed to represent the inter-teeth shape correlation. By matching the CSM to the patient's oral scan, the optimal crown shape is estimated to coincide with the surrounding teeth. Next, the crown is seamlessly integrated into the finish line of preparation via a surface warping step. Finally, porous internal supporting structures of the crown are generated to avoid excessive localized stresses. This algorithm is validated on clinical oral scan data and achieved less than 2 mm mean surface distance as compared to the manual designs of experienced human operators. The mechanical simulation was conducted to prove that the internal supporting structures lead to uniform stress distribution all over the model.

Estimation of the biomechanical mammographic deformation of the breast using machine learning models.

BACKGROUND: A typical problem in the registration of MRI and X-ray mammography is the nonlinear deformation applied to the breast during mammography. We have developed a method for virtual deformation of the breast using a biomechanical model automatically constructed from MRI. The virtual deformation is applied in two steps: unloaded state estimation and compression simulation. The finite element method is used to solve the deformation process. However, the extensive computational cost prevents its usage in clinical routine. METHODS: We propose three machine learning models to overcome this problem: an extremely randomized tree (first model), extreme gradient boosting (second model), and deep learning-based bidirectional long short-term memory with an attention layer (third model) to predict the deformation of a biomechanical model. We evaluated our methods with 516 breasts with realistic compression ratios up to 76%. FINDINGS: We first applied one-fold validation, in which the second and third models performed better than the first model. We then applied ten-fold validation. For the unloaded state estimation, the median RMSE for the second and third models is 0.8 mm and 1.2 mm, respectively. For the compression, the median RMSE is 3.4 mm for both models. We evaluated correlations between model accuracy and characteristics of the clinical datasets such as compression ratio, breast volume, and tissue types. INTERPRETATION: Using the proposed models, we achieved accurate results comparable to the finite element model, with a speedup of factor 240 using the extreme gradient boosting model. These proposed models can replace the finite element model simulation, enabling clinically relevant real-time application.

Case study: The influence of Achilles tendon rupture on knee joint stress during counter-movement jump - Combining musculoskeletal modeling and finite element analysis.

Background: Presently, the current research concerning Achilles tendon rupture repair (ATR) is predominantly centered on the ankle joint, with a paucity of evidence regarding its impact on the knee joint. ATR has the potential to significantly impede athletic performance and increase tibiofemoral contact forces in athletes. The purpose of this study was to prognosticate the distribution of stress within the knee joint during a countermovement jump through the use of a simulation method that amalgamated a musculoskeletal model of a patient who underwent Achilles tendon rupture repair with a finite element model of the knee joint. Methods: A male elite badminton player who had suffered an acute Achilles tendon rupture in his right leg one year prior was selected as our study subject. In order to analyze his biomechanical data, we employed both the OpenSim musculoskeletal model and finite element model to compute various parameters such as joint angles, joint moments, joint contact forces, and the distribution of knee joint stress. Results: During the jumping phase, a significantly lower knee extension angle (p < 0.001), ankle dorsiflexion angle (p = 0.002), peak vertical ground reaction force (p < 0.001), and peak tibiofemoral contact force (p = 0.009) were observed on the injured side than on the uninjured side. During the landing phase, the ankle range of motion (ROM) was significantly lower on the injured side than on the uninjured side (p = 0.009), and higher peak vertical ground reaction forces were observed (p = 0.012). Additionally, it is logical that an injured person will put higher load on the uninjured limb, but the finite element analysis indicated that the stresses on the injured side of medial meniscus and medial cartilage were significantly greater than the uninjured side. Conclusions: An Achilles tendon rupture can limit ankle range of motion and lead to greater joint stress on the affected area during countermovement jumps, especially during the landing phase. This increased joint stress may also transfer more stress to the soft tissues of the medial knee, thereby increasing the risk of knee injury. It is worth noting that this study only involves the average knee flexion angle and load after ATR in one athlete. Caution should be exercised when applying the conclusions, and in the future, more participants should be recruited to establish personalized knee finite element models to validate the results.

Dynamic 3D Modeling for Human Sperm Motility through the Female Cervical Canal and Uterine Cavity to Predict Sperm Chance of Reaching the Oocyte.

Sperm motility in the female genital tract is a key factor in the natural selection of competent cells that will produce a healthy offspring. We created a dynamic three-dimensional (3D) mechanical model of human sperm cells swimming inside cervical canal and uterine cavity dynamic 3D models, all generated based on experimental studies. Using these simulations, we described the sperm cells' behaviors during swimming inside the 3D tract model as a function of 3D displacement and time. We evaluated normal- and abnormal-morphology sperm cells according to their chances of reaching the oocyte site. As expected, we verified that the number of normal sperm cells that succeeded in reaching the fallopian tube sites is greater than the number of abnormal sperm cells. However, interestingly, after inspecting various abnormal sperm cells, we found out that their scores changed compared to swimming in an infinite medium, as is the case with in vitro fertilization. Thus, the interactions of abnormal sperm cells and the complicated geometry and dynamics of the uterus are significant factors in the filtering of abnormal sperm cells until they reach the oocyte site. Our study provides an advanced tool for sperm analysis and selection criteria for fertility treatments.

Influence of rotator cuff preload on fracture configuration in proximal humerus fractures: a proof of concept for fracture simulation.

INTRODUCTION: In regard of surgical training, the reproducible simulation of life-like proximal humerus fractures in human cadaveric specimens is desirable. The aim of the present study was to develop a technique that allows simulation of realistic proximal humerus fractures and to analyse the influence of rotator cuff preload on the generated lesions in regards of fracture configuration. MATERIALS AND METHODS: Ten cadaveric specimens (6 left, 4 right) were fractured using a custom-made drop-test bench, in two groups. Five specimens were fractured without rotator cuff preload, while the other five were fractured with the tendons of the rotator cuff preloaded with 2 kg each. The humeral shaft and the shortened scapula were potted. The humerus was positioned at 90° of abduction and 10° of internal rotation to simulate a fall on the elevated arm. In two specimens of each group, the emergence of the fractures was documented with high-speed video imaging. Pre-fracture radiographs were taken to evaluate the deltoid-tuberosity index as a measure of bone density. Post-fracture X-rays and CT scans were performed to define the exact fracture configurations. Neer's classification was used to analyse the fractures. RESULTS: In all ten cadaveric specimens life-like proximal humerus fractures were achieved. Two III-part and three IV-part fractures resulted in each group. The preloading of the rotator cuff muscles had no further influence on the fracture configuration. High-speed videos of the fracture simulation revealed identical fracture mechanisms for both groups. We observed a two-step fracture mechanism, with initial impaction of the head segment against the glenoid followed by fracturing of the head and the tuberosities and then with further impaction of the shaft against the acromion, which lead to separation of the tuberosities. CONCLUSION: A high energetic axial impulse can reliably induce realistic proximal humerus fractures in cadaveric specimens. The preload of the rotator cuff muscles had no influence on initial fracture configuration. Therefore, fracture simulation in the proximal humerus is less elaborate. Using the presented technique, pre-fractured specimens are available for real-life surgical education. LEVEL OF EVIDENCE: III.

The effect of the 2-UPS/RR ankle rehabilitation robot with coupling biomechanical model on muscle behaviors.

With the popularization of biomechanical simulation technology, aiming at the rehabilitation of ankle joint injury, we imported simplified model of proposed 2-UPS/RR (two identical unconstraint kinematic branches with a universal-prismatic-spherical (UPS) structure and two rotating pair (R)) ankle rehabilitation robot into AnyBody Modeling System. Therefore, a human-machine model was established using the HILL-type muscle model and muscle recruitment criteria. This paper investigated the effects of rehabilitation trajectories on biomechanical response during rehabilitation. Additionally, three main lower limb muscles (soleus, peroneal brevis, and extensor digitorum longus) were examined under different rehabilitation trajectories (plantar dorsiflexion, varus or valgus, and compound movement) in the present study. Based on the biomechanical response of lower limbs, the results showed that different muscles had different sensitivities to the change of rehabilitation trajectories. The correlation coefficient between joint force and plantar dorsiflexion angle reached 0.99 (P < 0.01), indicating that the change of joint force was mainly dominated by plantar dorsiflexion/plantar flexion, but also affected by varus or valgus. Safe rehabilitation training can be achieved by controlling the designed 2-UPS/RR rehabilitation robot. The behavior of muscle force and joint force under different rehabilitation trajectories can meet the needs of rehabilitation and treatment of joint diseases, and provide more reasonable suggestions for early rehabilitation.

Personalisation of Plantarflexor Musculotendon Model Parameters in Children with Cerebral Palsy.

Neuromusculoskeletal models can be used to evaluate aberrant muscle function in cerebral palsy (CP), for example by estimating muscle and joint contact forces during gait. However, to be accurate, models should include representative musculotendon parameters. We aimed to estimate personalised parameters that capture the mechanical behaviour of the plantarflexors in children with CP and typically developing (TD) children. Ankle angle (using motion capture), torque (using a load-cell), and medial gastrocnemius fascicle lengths (using ultrasound) were measured during slow passive ankle dorsiflexion rotation for thirteen children with spastic CP and thirteen TD children. Per subject, the measured rotation was input to a scaled OpenSim model to simulate the torque and fascicle length output. Musculotendon model parameters were personalised by the best match between simulated and experimental torque-angle and fascicle length-angle curves according to a least-squares fit. Personalised tendon slack lengths were significantly longer and optimal fibre lengths significantly shorter in CP than model defaults and than in TD. Personalised tendon compliance was substantially higher in both groups compared to the model default. The presented method to personalise musculotendon parameters will likely yield more accurate simulations of subject-specific muscle mechanics, to help us understand the effects of altered musculotendon properties in CP.

Prediction of post-operative adding-on or compensatory lumbar curve correction after anterior vertebral body tethering.

PURPOSE: Anterior Vertebral Body Tethering (AVBT), a fusionless surgical technique based on growth modulation, aims to correct pediatric scoliosis over time. However, medium-term curvature changes of the non-instrumented distal lumbar curve remains difficult to predict. The objective was to biomechanically analyze the level below the LIV to evaluate whether adding-on or compensatory lumbar curve after AVBT can be predicted by intervertebral disc (ID) wedging and force asymmetry. METHODS: 33 retrospective scoliotic cases instrumented with AVBT were used to computationally simulate their surgery and 2-year post-operative growth modulation using a finite element model. The cohort was divided into two subgroups according to the lumbar curvature evolution over 2 years: (1) correction > 10° (C); (2) maintaining ± 10° (M). The lumbar Cobb angle and residual ID wedging angle under LIV were measured. Simulated pressures and moments at the superior endplate of LIV + 1 were post-processed. These parameters were correlated at 2 years postoperatively. FINDINGS: On average, the LIV + 1 simulated moment was 538 Nmm for subgroup C, 155 Nmm for subgroup M with lumbar Cobb angle > 20° and 34 Nmm for angle < 20° whereas the ID angle was 1° for C and 0° for M. INTERPRETATION: On average, a positive moment on the LIV + 1 superior growth plate led to correction of the lumbar curvature, whereas a null moment kept it stable, and a parallel immediate postoperative ID under LIV contributed to its correction or preservation. Nevertheless, the significant interindividual variability suggested that other parameters are involved in the distal non-instrumented curvature evolution. LEVEL OF EVIDENCE: IV.

Finite element method for estimation of applanation force and to study the influence of intraocular pressure of eye on tonometry.

PURPOSE: Discover the associations of force of applanation on the eye with the plunging depth of the cornea and quantify them. The results will be utilized as the feedback parameter in the new prototype development of eye care instruments as additional force may damage the internal structure of the eye or may result in erroneous output. METHOD: A finite element-based eye model is designed utilizing the actual dimensions of the human eye. A standardized tonometer is designed and the simulation is carried out at predetermined deformation of the cornea to find the force of applanation on the cornea during tonometry. Adding on, the influence of IOP during tonometry is analyzed for a range of plunging depths of the cornea. RESULTS: The graphical results inferred the linear relation between the force of applanation with the deformation of the cornea and the results are quantified. The resulting deformation and stress plot of FEM based simulation approach is analyzed and observations regarding deformations and stress are made. CONCLUSION: The human eye is successfully developed and also computed force on the cornea during tonometry is validated. The inference drawn from the deformation plot and stress plot is that the junction of cornea-sclera along with cornea-tonometer periphery undergo maximum deformation and experiences the highest stress compared to other areas of the eye while during tonometry.

Consideration of specific key points improves outcome of decompression treatment in patients with endocrine orbitopathy: pre-/post-OP comparison and biomechanical simulation.

Endocrine orbitopathy is typically treated by resecting orbital walls. This procedure reduces intraorbital pressure by releasing intraorbital tissue, effectively alleviating the symptoms. However, selection of an appropriate surgical plan for treatment of endocrine orbitopathy requires careful consideration because predicting the effects of one-, two-, or three-wall resections on the release of orbital tissues is difficult. Here, based on our experience, we describe two specific orbital sites ('key points') that may significantly improve decompression results. Methodological framework of this work is mainly based on comparative analysis pre- and post-surgery tomographic images as well as image- and physics-based simulation of soft tissue outcome using the finite element modelling of mechanical soft tissue behaviour. Thereby, the optimal set of unknown modelling parameters was obtained iteratively from the minimum difference between model predictions and post-surgery ground truth data. This report presents a pre-/post-surgery study indicating a crucial role of these particular key points in improving the post-surgery outcome of decompression treatment of endocrine orbitopathy which was also supported by 3D biomechanical simulation of alternative two-wall resection plans. In particular, our experimental results show a nearly linear relationship between the resection area and amount of tissue released in the extraorbital space. However, a disproportionately higher volume of orbital outflow could be achieved under consideration of the two special key points. Our study demonstrates the importance of considering natural biomechanical obstacles to improved outcomes in two-wall resection treatment of endocrine orbitopathy. Further investigations of alternative surgery scenarios and post-surgery data are required to generalize the insights of this feasibility study.

Capturing contact in mitral valve dynamic closure with fluid-structure interaction simulation.

PURPOSE: Realistic fluid-structure interaction (FSI) simulation of the mitral valve opens the way toward planning for surgical repair. In the literature, blood leakage is identified by measuring the flow rate, but detailed information about closure efficiency is missing. We present in this paper an FSI model that improves the detection of blood leakage by building a map of contact. METHODS: Our model is based on the immersed boundary method that captures a map of contact and perfect closure of the mitral valve, without the presence of orifice holes, which often appear with existing methods. We also identified important factors influencing convergence issues. RESULTS: The method is demonstrated in three typical clinical situations: mitral valve with leakage, bulging, and healthy. In addition to the classical ways of evaluating MV closure, such as stress distribution and flow rate, the contact map provides easy detection of leakage with identification of the sources of leakage and a quality assessment of the closure. CONCLUSIONS: Our method significantly improves the quality of the simulation and allows the identification of regurgitation as well as a spatial evaluation of the quality of valve closure. Comparably fast simulation, ability to simulate large deformation, and capturing detailed contact are the main aspects of the study.

Applying Machine Learning to Finger Movements Using Electromyography and Visualization in Opensim.

Electromyographic signals have been used with low-degree-of-freedom prostheses, and recently with multifunctional prostheses. Currently, they are also being used as inputs in the human-computer interface that controls interaction through hand gestures. Although there is a gap between academic publications on the control of an upper-limb prosthesis developed in laboratories and its service in the natural environment, there are attempts to achieve easier control using multiple muscle signals. This work contributes to this, using a database and biomechanical simulation software, both open access, to seek simplicity in the classifiers, anticipating their implementation in microcontrollers and their execution in real time. Fifteen predefined finger movements of the hand were identified using classic classifiers such as Bayes, linear and quadratic discriminant analysis. The idealized movements of the database were modeled with Opensim for visualization. Combinations of two preprocessing methods-the forward sequential selection method and the feature normalization method-were evaluated to increase the efficiency of these classifiers. The statistical methods of cross-validation, analysis of variance (ANOVA) and Duncan were used to validate the results. Furthermore, the classifier with the best recognition result was redesigned into a new feature space using the sparse matrix algorithm to improve it, and to determine which features can be eliminated without degrading the classification. The classifiers yielded promising results-the quadratic discriminant being the best, achieving an average recognition rate for each individual considered of 96.16%, and with 78.36% for the total sample group of the eight subjects, in an independent test dataset. The study ends with the visual analysis under Opensim of the classified movements, in which the usefulness of this simulation tool is appreciated by revealing the muscular participation, which can be useful during the design of a multifunctional prosthesis.

Musculoskeletal biomechanics of patients with or without adjacent segment degeneration after spinal fusion.

STUDY DESIGN: A retrospective, single center, case-control study was performed. OBJECTIVE: The present study employed patient-specific biomechanical modeling to find potential biomechanical differences after spinal fusion at L4/5 in patients with and without subsequent development of adjacent segment disease (ASD). METHODS: The study population comprised patients who underwent primary spinal fusion at L4/5 and were either asymptomatic during > 4 years of follow-up (CTRL; n = 18) or underwent revision surgery for ASD at L3/4 (n = 20). Landmarks were annotated on preoperative and follow-up lateral radiographs, and specific musculoskeletal models were created using a custom-built modeling pipeline. Simulated spinal muscle activation and lumbar intervertebral shear loads in unfused segments were analyzed in upright standing and forward flexion. Differences between the pre- and postoperative conditions were computed for each patient. RESULTS: The average postoperative muscle activity in the upright standing posture was 88.4% of the preoperative activity in the CTRL group (p <  0.0001), but did not significantly change from pre- to postoperatively in the ASD group (98.0%). The average shear load magnitude at the epifusional joint L3/4 during upright standing increased from pre- to postoperatively in the ASD group (+ 3.9 N, +/- 17.4 (n = 18)), but decreased in the CTRL group (- 4.6 N, +/- 23.3 (n = 20); p <  0.001). CONCLUSION: Patient-specific biomechanical simulation revealed that spinal fusion surgery resulted in greater shear load magnitude and muscle activation and therefore greater forces at the epifusional segment in those with ASD compared with those without ASD. This is a first report of patient-specific disc load and muscle force calculation with predictive merits for ASD.

The Biomechanical Mechanism of Upper Airway Collapse in OSAHS Patients Using Clinical Monitoring Data during Natural Sleep.

Obstructive sleep apnea hypopnea syndrome (OSAHS) is a common sleep disorder characterized by repeated pharyngeal collapse with partial or complete obstruction of the upper airway. This study investigates the biomechanics of upper airway collapse of OSASH patients during natural sleep. Computerized tomography (CT) scans and data obtained from a device installed on OSASH patients, which is comprised of micro pressure sensors and temperature sensors, are used to develop a pseudo three-dimensional (3D) finite element (FE) model of the upper airway. With consideration of the gravity effect on the soft palate while patients are in a supine position, a fluid-solid coupling analysis is performed using the FE model for the two respiratory modes, eupnea and apnea. The results of this study show that the FE simulations can provide a satisfactory representation of a patient's actual respiratory physiological processes during natural sleep. The one-way valve effect of the soft palate is one of the important mechanical factors causing upper airway collapse. The monitoring data and FE simulation results obtained in this study provide a comprehensive understanding of the occurrence of OSAHS and a theoretical basis for the individualized treatment of patients. The study demonstrates that biomechanical simulation is a powerful supplementation to clinical monitoring and evaluation.

Automatic extraction of the mitral valve chordae geometry for biomechanical simulation.

PURPOSE: Mitral valve computational models are widely studied in the literature. They can be used for preoperative planning or anatomical understanding. Manual extraction of the valve geometry on medical images is tedious and requires special training, while automatic segmentation is still an open problem. METHODS: We propose here a fully automatic pipeline to extract the valve chordae architecture compatible with a computational model. First, an initial segmentation is obtained by sub-mesh topology analysis and RANSAC-like model-fitting procedure. Then, the chordal structure is optimized with respect to objective functions based on mechanical, anatomical, and image-based considerations. RESULTS: The approach has been validated on 5 micro-CT scans with a graph-based metric and has shown an [Formula: see text] accuracy rate. The method has also been tested within a structural simulation of the mitral valve closed state. CONCLUSION: Our results show that the chordae architecture resulting from our algorithm can give results similar to experienced users while providing an equivalent biomechanical simulation.

Planning acetabular fracture reduction using a patient-specific biomechanical model: a prospective and comparative clinical study.

PURPOSE: A simple, patient-specific biomechanical model (PSBM) is proposed in which the main surgical tools and actions can be simulated, which enables clinicians to evaluate different strategies for an optimal surgical planning. A prospective and comparative clinical study was performed to assess early clinical and radiological results. METHODS: From January 2019 to July 2019, a PSBM was created for every operated acetabular fracture (simulation group). DICOM data were extracted from the pre-operative high-resolution CT scans to build a 3D model of the fracture using segmentation methods. A PSBM was implemented in a custom software allowing a biomechanical simulation of the surgery in terms of reduction sequences. From July 2019 to December 2019, every patient with an operated for acetabular fracture without PSBM was included in the standard group. Surgery duration, blood loss, radiological results and per-operative complications were recorded and compared between the two groups. RESULTS: Twenty-two patients were included, 10 in the simulation group and 12 in the standard group. The two groups were comparable regarding age, time to surgery, fracture pattern distribution and surgical approaches. The mean operative time was significantly lower in the simulation group: 113 min ± 33 (60-180) versus 184 ± 58 (90-260), p = 0.04. The mean blood loss was significantly lower in the simulation group, p = 0.01. No statistical significant differences were found regarding radiological results (p = 0.16). No per-operative complications were recorded. CONCLUSION: This study confirms that pre-operative planning in acetabular surgery based on a PSBM results in a shorter operative time and a reduction of blood loss during surgery. This study also confirms the feasibility of PSBM planning in daily clinical routine. LEVEL OF EVIDENCE: II: prospective study.

Proposal and validation of polyconvex strain-energy function for biological soft tissues.

BACKGROUND: Mechanical simulations for biological tissues are effective technology for development of medical equipment, because it can be used to evaluate mechanical influences on the tissues. For such simulations, mechanical properties of biological tissues are required. For most biological soft tissues, stress tends to increase monotonically as strain increases. OBJECTIVE: Proposal of a strain-energy function that can guarantee monotonically increasing trend of biological soft tissue stress-strain relationships and applicability confirmation of the proposed function for biological soft tissues. METHOD: Based on convexity of invariants, a polyconvex strain-energy function that can reproduce monotonically increasing trend was derived. In addition, to confirm its applicability, curve-fitting of the function to stress-strain relationships of several biological soft tissues was performed. RESULTS: A function depending on the first invariant alone was derived. The derived function does not provide such inappropriate negative stress in the tensile region provided by several conventional strain-energy functions. CONCLUSIONS: The derived function can reproduce the monotonically increasing trend and is proposed as an appropriate function for biological soft tissues. In addition, as is well-known for functions depending the first invariant alone, uniaxial-compression and equibiaxial-tension of several biological soft tissues can be approximated by curve-fitting to uniaxial-tension alone using the proposed function.

Real-time biomechanics using the finite element method and machine learning: Review and perspective.

PURPOSE: The finite element method (FEM) is the preferred method to simulate phenomena in anatomical structures. However, purely FEM-based mechanical simulations require considerable time, limiting their use in clinical applications that require real-time responses, such as haptics simulators. Machine learning (ML) approaches have been proposed to help with the reduction of the required time. The present paper reviews cases where ML could help to generate faster simulations, without considerably affecting the performance results. METHODS: This review details the ML approaches used, considering the anatomical structures involved, the data collection strategies, the selected ML algorithms, with corresponding features, the metrics used for validation, and the resulting time gains. RESULTS: A total of 41 references were found. ML algorithms are mainly trained with FEM-based simulations in 32 publications. The preferred ML approach is neural networks, including deep learning in 35 publications. Tissue deformation is simulated in 18 applications, but other features are also considered. The average distance error and mean squared error are the most frequently used performance metrics, in 14 and 17 publications, respectively. The time gains were considerable, going from hours or minutes for purely FEM-based simulations to milliseconds, when using ML. CONCLUSIONS: ML algorithms can be used to accelerate FEM-based biomechanical simulations of anatomical structures, possibly reaching real-time responses. Fast and real-time simulations of anatomical structures, generated with ML algorithms, can help to reduce the time required by FEM-based simulations and accelerate their adoption in the clinical practice.